About the position

At the Department of Plant Sciences (IPV), Faculty of Biosciences (BIOVIT), we have an exciting opportunity for a Postdoctoral Fellow in Computational Plant Genetics and Digital Twin Modelling. The position is a three-year, fixed-term appointment funded through the NMBU PheNo infrastructure and embedded in the TWIN-NUE project: TraitFinder-enabled Digital Twins and Genomics for Nitrogen Use Efficiency (NUE) in Oat and Perennial Ryegrass.

PheNo is a cutting-edge infrastructure dedicated to plant phenotyping in Norway funded by NFR for 5 years. Designed to support advanced research in plant biology, agriculture, and climate adaptation, this new facility will provide tools and technologies for high-throughput and precision phenotyping. By enabling detailed observation and analysis of plant traits under various environmental conditions, our infrastructure promotes innovation and collaboration among researchers, breeders, farmers and industry partners. Together, we aim to strengthen the sustainability of Norwegian agriculture to face internal and global challenges.

As a postdoc, your role will be central to developing AI-driven digital twins that simulate and predict nitrogen use efficiency (NUE) in forage grasses and oats. By combining high-resolution phenotyping data from the TraitFinder system, drones, and robotic sensors with genomic and transcriptomic datasets, you will help establish a new framework for predictive phenomics.

The project offers a unique opportunity to link advanced modelling with plant genetics, strengthening NMBU’s position at the forefront of next-generation crop science, and contributing to more sustainable nitrogen management and breeding strategies for future agriculture.

This position offers a unique opportunity to:

Play a central role in an ambitious research project that turns a state-of-the-art measurement facility (TraitFinder) into a predictive decision hub.
Access unique, high-resolution datasets from the PheNo infrastructure and its TraitFinder system.
Contribute to high-impact publications.
Work in a vibrant, international, and collaborative environment alongside experts in plant genetics, phenomics, agricultural robotics, and data science.
Participate in international research stays.
Participate in research, teaching, and technical development activities.
Join an extensive national phenotyping network, with NMBU serving as a key node.

The working languages are both Norwegian and English.

Main tasks

The main purpose of the post-doctoral position is to qualify for work in high-level scientific positions. A PhD degree is required.

Develop protocols for real-time phenotyping of NUE-related traits using the TraitFinder phenotyping system.
Build and validate digital twin models using 3D point cloud and multispectral data, applying ML methods (e.g. XGBoost, LSTM, CNN).
Run virtual “what-if” scenarios for nutrient, water, and light inputs to predict biomass, canopy, protein content and chlorophyll dynamics.
Validate models using greenhouse and field trial data from UAVs, LiDAR robots, and in-soil sensors.
Perform genome-to-phenome analyses to reveal key loci and expression signals for NUE traits
Apply digital twins for functional validation of CRISPR-edited NUE mutants in perennial ryegrass.
Publish findings in peer-reviewed journals and contribute to teaching/supervision in phenomics and modelling as part of PheNo infrastructure.
Participate as co-supervisor for master's / PhD students in the project.

Competence

Required qualifications

A Norwegian doctoral degree in the relevant subject area or an equivalent foreign doctoral degree approved as equivalent to a Norwegian doctoral degree
Applicants must have a relevant PhD degree in plant sciences, computational biology, bioinformatics, data science, or related field.
Documented expertise in machine learning and time-series modelling (e.g. LSTM, XGBoost, CNN).
Strong programming skills in languages such as Python and R.
Experience with phenotyping data (imaging, 3D point clouds, or multispectral data).
Good presentation skills, written and oral in English

Qualifications considered an advantage

Background in plant genetics/genomics/phenomics (SNP analysis/transcriptomics/image analysis).
Experience working with forage crops or cereals.
Knowledge of digital phenotyping systems (e.g. UAVs, TraitFinder, IoT sensors).
Ability to collaborate in interdisciplinary teams across plant science, robotics/sensors, and AI modelling
Knowledge of developing scientific software tools, databases, or apps for data analysis and visualization.

Personal qualities

Strong motivation for interdisciplinary plant research
Interest and motivation in teaching and teaching development
Ability and willingness to initiate, form and carry out research projects
Ability to take initiative and work systematically and efficiently, both independently and in teams
Good communication and dissemination skill
Positive and solution-oriented

Remuneration and further information

The position is placed in position code 1352 Postdoctoral Fellow (NOK 604 900-750 000) depending on qualifications. For particularly well-qualified applicants, a higher salary may be considered. The position follows ordinary meriting regulations.

Interested in learning more about the position? Contact Research Scientist: Mallikarjuna Rao Kovi phone: +47 40566127, (e-mail: mallikarjuna.rao.kovi@nmbu.no) and Professor: Morten Lillemo phone: tel: +4767232775, (e-mail:morten.lillemo@nmbu.no">20morten.lillemo@nmbu.no" rel="nofollow"> morten.lillemo@nmbu.no).

Information to applicants

Application

Send application electronically via the link "Apply for this job" at the top of this page. This will route you to the University's Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form.

Application Deadline: 22/10/2025

Your CV must be entered in Jobbnorge's CV form and not just included as an attachment. This is in order to be able to comply with the regulations to the Public Administration Act §15.

The following must be included in the application:

Cover letter
CV
Copies of diplomas and other relevant certificates
Up to ten publications selected by the applicant as most relevant must be attached to the application. If it is difficult to identify the contribution of the applicant in multiple-author publications, a short explanation about the applicant’s part of the work is suggested.
Names and contact details for two references

Applicants invited for an interview will be asked to present verified copies of diplomas and certificates.

Documents that cannot be sent electronically are sent in triplicate by ordinary mail marked still.nr. 25/05132 to NMBU, Faculty of Biosciences, P.O. Box 5003, NO-1432 Ås, within 22.10.2025.

Please note that the report from the expert committee will be sent to all applicants.

About The Faculty of Biosciences

The Faculty of Biosciences (BIOVIT) aims to shape the future of food and bioproduction through teaching and research in biology and sustainable production and use of plants, livestock and fish. The faculty has a large project portfolio and an annual turnover of approximately NOK 250 million.

BIOVIT is organized into seven research groups: Genome Biology, Breeding, Genetics and Food Production Systems, Ruminant Nutrition and Physiology, Ethology and Animal Welfare, Nutrition and Physiology for Monogastric Animals, Plant Biology, Sustainable Food Systems and Integrated Plant Protection, and Genetics, Evolution and Sustainable Plant Production. Additionally, the faculty has seven research support and laboratory units.

BIOVIT is responsible for bachelor’s and master’s programs in aquaculture, biology, animal science, and plant science, as well as English-language master’s programs in Agroecology, Plant Sciences, Feed Manufacturing Technology, and Genome Sciences. BIOVIT also offers Ph.D. programs in animal science and plant science. Currently, the faculty has about 550 bachelor’s and master’s students and 90 Ph.D. students. BIOVIT employs approximately 230 staff members and has its own faculty administration.

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